INTERNATIONAL JOURNAL OF eBUSINESS and eGOVERNMENT STUDIES
Vol: 12 No: 2 Year: 2020 ISSN: 2146-0744 (Online) (pp. 107-121) Doi: 10.34111/ijebeg.202012202
Recieved: 11.09.2019 | Accepted: 04.02.2020 | Published Online: 01.07.2020
-RESEARCH ARTICLE-
Citation (APA): Muller, C. & Klerk, N, D., (2020), Influence of Design Aesthetics and Brand Name on
Generation Y Students’ Intention to Use Wearable Activity-Tracking Devices, International Journal of
eBusiness and eGovernment Studies, 12 (2): 107-121. Doi: 10.34111/ijebeg.202012202
107
INFLUENCE OF DESIGN AESTHETICS AND BRAND NAME ON
GENERATION Y STUDENTS’ INTENTION TO USE WEARABLE
ACTIVITY-TRACKING DEVICES
Chantel Muller
North-West University
E-mail: [email protected]
Orcid ID: 0000-0002-2470-3902
Natasha de Klerk
North-West University
E-mail: [email protected]
Orcid ID: 0000-0001-7223-0006
─Abstract─
Wearable activity-tracking devices such as pedometers, fitness bands and watches,
heart-rate monitoring chest straps and armbands, various types of activity-sensing
clothing and the like, are increasing in popularity amongst consumers on a global
scale. Among all wearable technology, fitness trackers remain the biggest
wearables category by unit sales in 2019, with an estimated revenue potential of
2.66 billion US dollars. However, despite this significant global interest, the
adoption rate of these devices is slow amongst South African consumers. The
consumer segment most likely to adopt a wearable activity tracker is young, high-
income individuals, which are epitomised by Generation Y consumers, especially
the student portion of this market segment since they are characterised by high
future earning probability. With the lack of research regarding the adoption of
wearable activity trackers, this study explores the influence of device design
aesthetics and brand name on Generation Y consumers’ intention to use wearable
activity trackers. A self-administered questionnaire was used to survey a non-
probability convenience sample of 480 students registered at three public South
African higher education institutions (HEIs) within the Gauteng province. A
descriptive research design and a quantitative research approach was followed,
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where the captured data were analysed using descriptive statistics, correlation
analysis, reliability and validity measures and structural equation modelling. The
findings indicate that design aesthetics and brand name significantly influence
Generation Y students’ intention to use wearable activity-tracking devices. A
device’s design aesthetics as well as brand name are significant in determining
Generation Y students’ intention to use such tracking devices. As such, retailers and
marketers should focus on enhancing design aesthetics and brand awareness of
wearable activity-tracking devices when targeting the lucrative Generation Y
student market segment.
Key Words: Wearable activity-tracking devices, Generation Y students, Intention
to use, South Africa
JEL Classification: M31, M37, O30
1. INTRODUCTION
A wearable activity-tracking device, also referred to as a fitness tracker, is an
electronic device that can be worn on the body to measure one’s fitness-related
movement and metrics in real time, whilst being able to connect to a computer or a
smart phone through wireless connectivity mediums for the purpose of displaying
and tracking the recorded information (Techopedia, 2018). Typically, these devices
make use of accelerometers, altimeters, sensors and algorithms to track the number
of steps taken, distance travelled, calories burnt (Beckham, 2012), record different
sport sessions (Hong, 2015), static or optical heart-rate data (Rettner, 2014), as well
as patterns and quality of sleep (Haslam, 2016). Wearable activity-tracking devices
pose important health and fitness benefits for the user. The recorded information
may be used to enhance lifestyle behaviours, such as becoming more active, as well
as adjusting one’s diet- and sleep regimen (Maher, Ryan, Ambrosi, & Edney, 2017).
Another advantage for users is to share the data with friends by means of text-
messaging or on social platforms, such as Endomondo, Strava, Facebook or
WhatsApp, where a competitive instinct impels better performance and results in
an ego boost, particularly when the device constantly commends the user for
achieving daily goals (Nield, 2017). In addition to promoting healthier lifestyles,
fitness trackers are used by consumers to make a fashion statement, which drives
the significant need for fashionable fitness trackers (Weingus, 2015).
Globally, activity-tracking devices are increasing in popularity amongst consumers,
which is evident in the significant size of the global fitness tracker market (Loomba
& Khairnar, 2018). Among all wearable technology, fitness trackers remain the
biggest wearables category by unit sales in 2019, with an estimated revenue
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Vol 12, No 2, 2020 ISSN: 2146-0744 (Online) Doi: 10.34111/ijebeg.202012202
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potential of 2.66 billion US dollars (CCS Insight, 2019), expected to reach 48.2
billion US dollars by 2023 (P&S Market Research, 2018). The continuous rise in
technological innovation, in addition to the increased health consciousness among
consumers, is likely to provide even more future growth opportunity for the fitness
tracker market (Loomba & Khairnar, 2018). In South Africa, the adoption rate of
these devices is slow amongst consumers. Less than 13 percent of South African
households owned some form of wearable technology in 2018. However, this
number is expected to increase as this technology becomes more widespread and
affordable (Business Tech, 2018). The recorded market penetration rate of 3.81
percent for wearable activity-tracking devices in 2017 is expected to increase to
4.83 percent by 2020 (Statista, 2018). Notably, the size and growth of the fitness
trackers market, both globally (Loomba & Khairnar, 2018), as well as in South
Africa (Business Tech, 2018) is dominated and driven by the youth, labelled as
Generation Y (Markert, 2004).
Understanding the Generation Y cohort, which includes individuals born between
1986 and 2005 (Markert, 2004), is essential for marketers and retailers (Smith,
2011). Generation Y is considered the largest consumer segment in the world (Fry,
2015) and is positioned to become the most affluent generation thus far (Cox,
Kilgore, Purdy & Sampath, 2008) with a high aggregate spending (Brown, 2015)
standing at 20 trillion US dollars in 2014 (Barmann, 2014). Individuals of
Generation Y, raised in a media- and information-saturated world, are regarded as
the most tech- and internet-savvy generation to date, with significantly high
technology adoption rates (Ferguson, 2008) and are viewed by marketers as being
fashion conscious (Cassidy & Van Schijndel, 2011), sophisticated and
consumption-orientated (Eastman & Liu, 2012). The significant size of the South
African Generation Y market segment, which comprised approximately 36 percent
of the country’s population in 2018 (Statistics South Africa, 2018), makes them
important to South African marketers and retailers, including those of activity-
tracking devices (Valaei & Nikhashemi, 2017). Generation Y members who have
engaged in tertiary education are important to marketers and retailers, since higher
education is associated with higher future earning potential and higher social
standing (Bevan-Dye & Surujlal, 2011). Typically, studies pertaining to university
students include individuals between 18 and 24 years (Kumar & Lim, 2008).
Consumer intent is an important behavioural aspect in understanding consumers’
behaviour (Ajzen, 1991). Described as the anticipated outcome that precedes
planned behaviour (Al-Debei, Al-Lozi & Papazafeiropoulou, 2013), behavioural
intention pertains to a consumer’s willingness to perform a certain behaviour (Chan
& Bishop, 2013). Importantly, an individual’s intention to perform a specific
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behaviour is dependent on the individual’s favourable evaluation of performing the
behaviour (Ajzen, 1991). Therefore, the higher a consumer’s intention is towards
using wearable activity-tracking devices, the more likely they will purchase such
devices. Studies pertaining to consumers’ attitudes and intention to use wearable
activity tracking devices (Chin, Johnson, & Schwarz, 2008; Wang, Dacko, & Gad,
2008; Yang, Yu, Zo & Choi, 2016) are limited. Furthermore, while there are studies
on the importance of design aesthetics (Jeong, Kim, Park & Choi, 2017) and brand
name (Yang et al., 2016) and the role they play in influencing consumers’ usage
intentions of new technologies, there is a lack of research on the influence of these
antecedents on Generation Y students’ intention to use wearable activity trackers
(Pateman, 2015). As such, the purpose of this study was to explore the influence of
device design aesthetics and brand name on Generation Y students’ intention to use
wearable activity trackers.
2. FACTORS THAT INFLUENCE INTENTION TO USE WEARABLE
ACTIVITY-TRACKING DEVICES
The marketing literature notes that both a product’s design aesthetics (Pateman,
2015) and brand name (Nordquist, 2017) are important tools for differentiating a
product from that of its competitors.
Design aesthetics is a key component influencing consumers’ product preferences
when making purchasing decisions (Schmitt & Simonson, 1997), including
selecting wearable activity-tracking devices (Pateman, 2015). The aesthetic design
of a product appeals to consumers’ senses, which influence their product
perceptions and decision-making. Therefore, design aesthetics is an essential
component of a company’s marketing strategy (Schmitt & Simonson, 1997). The
word aesthetics relates to the perception by one’s senses (Ford, 2009), as derived
from the ancient Greek term for perception, namely aisthesis and refers to the
principles that oversee the nature and appreciation of beauty (Encyclopedia of Art
Education, 2017). In a modern view, aesthetics is used to characterise a specific
style or design (Ford, 2009) and is an individual’s understanding of what is beautiful
(Pateman, 2015).
In this study, design aesthetics refers to how wearable activity-tracking devices are
perceived to appear overall, with specific reference to the shape, colour and style,
measuring the degree to which these devices are perceived to be attractive, stylish,
trendy, sleek and sophisticated. A stylish design describes a device that has a high
quality appearance (Cambridge Dictionary, 2017), whereas a trendy design is one
that is modern and influenced by the most recent fashion or ideas. When referring
to an item of clothing or accessory to one’s attire, the word sleek is commonly used
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and refers to the smoothness of the design as opposed to a more rugged, bulky and
striped look and feel (Walter, 2009). A sophisticated design refers to clothes and
accessories that are streamlined, refined and tailored, flawlessly fits the user, with
clean-cut and invigorating colour combinations (Cox, 2008). Evidently, design
aesthetics regarding technological devices, refers to the degree of perceived device
attractiveness. For the purpose of this study, design aesthetics is theorised to
influence consumers’ intention to use wearable activity-tracking devices. It is
believed that if the device design aesthetics are perceived to be high, it will have a
positive influence on consumers’ intention towards using wearable activity-
tracking devices.
The name or title given to a specific product or service by the manufacturer or
organisation is referred to as the brand name. Brand names help consumers to
identify and differentiate one product from another and can be protected by a
trademark (™) (Nordquist, 2017). According to Yang et al. (2016), brand name is
a key element when selecting a wearable activity-tracking device, as it reflects the
quality of a wearable activity-tracking device and reduces the possible risk often
associated with purchasing new technology. Viewed as a social indicator, brand
name is widely acknowledged as an important motivating factor in consumer
decision-making (Hillenbrand, Alcauter, Cervantes, & Barrios, 2013) and provides
a way to both express and increase one’s self-image (Yang et al., 2016), as well as
allow the consumer to identify themselves with the brand and express status and
social identification (Del Río, Vázquez & Iglesias, 2001). When faced with
uncertainty when evaluating products, brand name is the foremost extrinsic signal
consumers use to assist with decision-making (Dawar & Parker, 1994). Moreover,
brand name is a crucial determinant of a new products’ success. When consumers
lack experience with a product, prior experience with known brand names offers
them a certain degree of familiarity (Grewal, Krishnan, Baker Borin, 1998). Owing
to wearable activity-tracking devices being relatively new in the South African
consumer market, it may be assumed that a well-known brand name is essential to
the adoption of such devices. Previous research found brand name to be a significant
influential factor on consumers’ decision making and purchase intention (Grewal
et al., 1998); hence, it is important to determine the influence of brand name on
Generation Y students’ intention to use wearable activity trackers.
3. METHODOLOGY
This study used a descriptive research design, following the single cross-sectional
approach.
3.1. Sampling method
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The target population for the study was defined as Generation Y university students
aged between 18 and 24 years, registered at public South African higher education
institutions (HEIs). From the initial sampling frame comprising the 26 registered
South African public HEIs (Business Tech, 2015), three campuses located in the
Gauteng province were selected, using judgement sampling. Thereafter, following
the mall-intercept approach, a non-probability convenience sample of 600 students
was drawn (200 per institution).
3.2. Research instrument and data collection
To collect the required data, a structured self-administered survey questionnaire
was used. This survey questionnaire comprised a section requesting the completion
of the sample participants’ demographic information as well as a section to which
participants had to respond to scaled questions based on previously published
studies. Design aesthetics (five items) was measured using the attractiveness scale
adapted from Nelson, Verhagen and Noordzij (2016); whereas, the three-item brand
name scale was adapted from Yang et al. (2016). Generation Y students’ intention
to use wearable activity-tracking devices (three items) was measured by adapting
the scale of Kim and Shin (2015). All scaled responses were measured on a six-
point Likert scale, ranging from strongly disagree (1) to strongly agree (6). After
permission was solicited from lecturers at each of the three HEI campuses,
questionnaires were distributed to those lecturers’ students for voluntary
completion. The captured data were analysed using the IBM Statistical Package for
Social Sciences (SPSS) and AMOS, Version 25 for Windows.
4. RESULTS
Of the 600 questionnaires distributed, 480 usable questionnaires were returned,
resulting in a response rate of 80 percent. A description of the sample participants
is outlined in Table 1.
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Table 1: Sample description Gender % Age % Province % Institution %
Male 40.2 18 20.6 Eastern Cape 4.0 Traditional 37.5
Female 59.4 19 27.9 Free State 6.7 Technology 37.3
Missing 0.4 20 17.7 Gauteng 52.3 Comprehensive 25.2
21 17.3 Kwazulu-Natal 4.4
22 9.0 Limpopo 17.5
23 5.0 Mpumalanga 7.7
24 2.5 North West 6.5
Northern Cape 0
Western Cape 0.6
Missing 0.4
The sample included participants from eight of South Africa’s nine provinces, with
no participants that originated from the Northern Cape and participants from each
of the seven age categories in the target population. The sample included more
female than male participants. Descriptive statistics and reliability coefficients were
computed, as well as Pearson’s product-moment correlation coefficients for each
pair of constructs. Table 2 presents these results.
Table 2: Descriptive statistics, reliability analysis and correlation coefficients Constructs Means Standard
deviations
Cronbach
alpha values
F1 F2
Design aesthetics 4.34 0.96 0.831
Brand name 4.69 1.10 0.841 0.178*
Intention to use 4.77 1.18 0.934 0.322* 0.349*
*Statistically significant at p≤0.01 (two-tailed)
As evident from Table 2, all Cronbach’s alpha values were above the satisfactory
minimum level of 0.70 (Zikmund & Babin, 2013), thereby indicting acceptable
internal consistency reliability. Mean values above 3.5 recorded on a six-point
Likert-type scale indicate that Generation Y students intend to use wearable
activity-tracking devices in the near future (mean = 4.77) and that the device’s
brand name (mean = 4.69) and design aesthetics (mean = 4.34) are both integral
factors when selecting such devices. Furthermore, as presented in Table 2, the
computed correlation coefficients indicate statistically significant (p≤0.01) and
positive relationships between each of the pairs of constructs, suggesting
nomological validity (Hair, Black, Babin & Anderson, 2019). Additionally, there
were no multicollinearity concerns since the collinearity diagnostics delivered a
tolerance value of 0.968 for both independent factors and an average variance
inflation factor (VIF) of 1.03. This indicates no issues of multicollinearity since
higher tolerance values (Hair et al., 2019) and a VIF below 10 (Burns & Bush,
2014) indicate a small degree of multicollinearity. The lack of multicollinearity
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concerns combined with the nomological validity of the measurement theory
allowed for structural equation modelling to be performed.
A three-factor measurement model was specified for confirmatory factor analysis
comprising design aesthetics (five items), brand name (three items) and intention to
use wearable activity-tracking devices (three items). The first loading on each of
the three factors was fixed at 1.0 for model identification purposes. As a result, there
were 66 distinct sample moments and 25 distinct parameters to be estimated,
leaving 41 degrees of freedom (df) based on an over-identified model. A chi-square
value of 145.44 was produced with a probability level equivalent to 0.001. The
model was inspected for any problematic estimates including standardised factor
loadings either above 1.0 or below -1.0 as well as negative error variance values,
construct reliability (CR) values, the average variance extracted (AVE) and the
squared root of the AVE (√AVE) – all of which were calculated to assess the
construct reliability and convergent validity of the measurement model (Hair et al.,
2019). These findings are illustrated in Table 3.
Table 3: Measurement model estimates Constructs Standard loading
estimates
Error variance
estimates
CR AVE √AVE
Design aesthetics (F1) 0.73 0.54 0.83 0.50 0.71
0.82 0.68
0.70 0.49
0.66 0.44
0.59 0.35
Brand name (F2) 0.83 0.69 0.85 0.65 081
0.88 0.78
0.69 0.48
Intention to use (F3) 0.90 0.80 0.93 0.82 0.91
0.92 0.86
0.90 0.81
Correlations F1↔F2: 0.20 F1↔F3: 0.37 F2↔F3: 0.39
As indicated in Table 3, there were no problematic estimates and statistically
significant relationships (p≤0.001) were calculated between each of the pairs of
factors. Moreover, the CR values above 0.70 demonstrate composite reliability
(Malhotra, 2010). Standardised factor loadings above 0.50 and AVE values equal
to or above 0.50 infer convergent validity, while the fact that the square root of each
of the AVE values exceeds the correlation coefficients gives evidence of
discriminant validity (Hair et al., 2019). The model fit was determined by assessing
the chi-square, the standardised root mean residual (SRMR), the root mean square
of approximation (RMSEA), the goodness of fit index (GFI), the incremental fit
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index (IFI), the Tucker-Lewis index (TLI) and the comparative fit index (CFI). A
good fit is indicated by a non-significant chi-square value with GFI, IFI, TLI and
CFI values exceeding 0.9 (preferably above 0.95) as well as a small SRMR and
RMSEA values of 0.08 or less (Hooper, Coughlan, & Mullen, 2008). Despite a
significant chi-square statistic [(145.44 (df = 41, p<0.000)], the measurement model
returned acceptable fit indices of SRMR = 0.04, RMSEA = 0.073, GFI = 0.95, IFI
= 0.96, TLI = 0.95 and CFI = 0.96. Based on this measurement model, a structural
model was constructed and tested. Table 4 shows the estimated standardised
regression coefficients.
Table 4: Standardised regression coefficients for the structural paths Paths β Unstandardised
β
Estimate
s
p-
values
Results
Design aesthetics → Intention to
use 0.31 0.37 0.098 0.001 Significant
Brand name → Intention to use 0.32 0.34 0.106 0.001 Significant
β: beta coefficient; SE: standard error; p: two-tailed statisical significance
Whilst the structural model returned a significant chi-square value [(145.44 (df=41,
p<0.000)], the model returned acceptable fit indices. The values comprised SRMR
= 0.04, RMSEA = 0.073, GFI = 0.95, IFI = 0.96, TLI = 0.95 and CFI = 0.96. Table
4 further indicates that both the paths tested were statistically significant (p≤0.01).
Design aesthetics (β = 0.31, p<0.001) and brand name (β = 0.32, p<0.001) have a
statistically significant positive influence on intention to use wearable activity-
tracking devices. The squared multiple correlation coefficient for intention to use is
0.24, demonstrating that design aesthetics and brand name collectively explain 24
percent of the variance in Generation Y students’ intention to use wearable activity
trackers. There is a possibility that other factors might contribute in explaining
Generation Y students’ intention to use such devices.
5. DISCUSSION
This study aimed to determine the influence of design aesthetics and brand name
on Generation Y students’ intention to use wearable activity-tracking devices.
Similar to previous studies that emphasise the importance of both variables
(Dehghani, 2018; Hernández & Küster, 2012; Grewal et al., 1998), the findings of
this study indicate that design aesthetics and brand name have a significant
influence on consumer’s intention towards wearable activity trackers. Despite the
known importance of the influence of brand name and design aesthetics on
consumer behaviour, this study is the first to link this importance to a largely under-
researched industry, namely wearable activity-tracking devices. This study
established that a device’s brand name significantly influences this cohort’s
C. Muller - N. Klerk
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intention to use wearable activity-tracking devices. This suggests that a reliable
brand name is a key factor to consider when choosing a device and reflects the
quality of a wearable activity-tracking device. Moreover, there appears to be less
risk of being disappointed when purchasing a device with a reliable brand name. As
such, a wearable activity-tracking device with a reliable brand name, that is
attractive, stylish-looking, trendy, sleek and sophisticated in design, will influence
Generation Y students’ intention to use such devices in the near future.
To this end, wearable activity-tracking device manufacturers, especially well
established and popular international companies, should note that the devices'
design aesthetics and the brand name are vital to South African Generation Y
students’ intention to adopt such devices and they should consider the above design
aesthetic factors when designing and manufacturing new devices to appeal to this
lucrative segment. Both local and international device manufacturers, retail outlets
and e-commerce sites, together with their marketing managers, should continuously
monitor this cohorts’ intention to use and subsequently purchase wearable activity-
tracking devices. These entities should continue to influence this Generation’s
intention to use wearable activity-tracking devices by manufacturing a device that
matches the needs of these consumers and constantly introducing new and
innovative models. Further initiatives include offering these devices on a trial basis,
implementing alternative payment methods and payment terms, such as on an
interest-free basis and continuously advocating the benefits of using these devices.
These efforts might encourage large-scale acquisition of wearable activity-tracking
devices among the target population based on their proven intent.
Like most studies, several limitations can be identified in this study. First, non-
probability convenience sampling was employed, therefore caution should be taken
in generalising the results to the target population. Secondly, the study used a single
cross-sectional research design, which merely provides a snapshot in time. Future
research, in the form of a longitudinal study, would provide valuable information
concerning any changes in Generation Y students’ intentions towards using
wearable activity-tracking devices.
6. CONCLUSION
Increasing the adoption rates of wearable activity-tracking devices among South
African consumers, subsequently leading to an economical boost, depends largely
on consumers’ acceptance of these technologies as well as the continuous efforts of
device manufacturers, retailers and e-commerce sites to market these devices to the
target population. The model empirically tested in this study concludes that design
aesthetics and brand name are crucial factors that influence Generation Y students’
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intention to use wearable activity-tracking devices. The marketing managers of
wearable activity-tracking device manufacturers, especially well established and
popular international companies, retailers as well as e-commerce sites in South
Africa and abroad, can use these findings to better comprehend Generation Y
students’ wearable activity-tracking device intent and subsequent usage and
formulate efficient, targeted strategies to increase the usage of these devices
amongst this lucrative target population.
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